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This study examined the effects of game schedule, travel demands and contextual factors on team game-related statistics during a full season. The top 10 teams competing in the 2020-2021 Euroleague basketball season were included where game-related statistics from their respective national competitions and the Euroleague competition were retrieved (761 games). Hierarchical linear regression models were computed to evaluate the effects of distance travelled, game schedule and contextual factors for the previous and current games (league, season phase, opponent level, game outcome, score differential) on key performance indicators (points, shooting, rebounds, assists, turnovers, fouls). Several significant models ( p  < 0.05) yielded R 2 values ranging from 0.05 to 0.22 with small -to- medium effect magnitudes. Analyses revealed significant associations between longer durations separating games and less free-throws being made and between further distances travelled and worse 3-point shooting, more offensive rebounds and more fouls. Regarding contextual factors, favourable outcomes for shooting, assists, steals, fouling and turnovers were significantly associated with team success. Playing higher-level teams and competing in playoffs or finals was associated with several diminished outcomes. These results emphasize the multi-factorial nature of performance in elite European basketball, with game schedule, travel and various contextual factors requiring consideration in developing holistic operational plans for teams.

Background: A large proportion of European children, adults and older adults do not engage in sufficient physical activity (PA). Understanding individual and contextual factors associated with PA behaviours is essential for the identification and implementation of effective preventative environments, policies, and programmes that can promote an active lifestyle across life course and can potentially improve health. The current paper intends to provide 1) a multi-disciplinary, Pan-European and life course view of key determinants of PA behaviours and 2) a proposal of how these factors may cluster., Methods: After gathering a list of 183 potential PA behaviours-associated factors and a consensus meeting to unify/consolidate terminology, a concept mapping software was used to collate European experts' views of 106 identified factors for youth (<19 years), adults (19-64 years), and older adults (≥65 years). The analysis evaluated common trends in the clustering of factors and the ratings of the distinct factors' expected modifiability and population-level impact on PA behaviours across the life course. Priority for research was also assessed for each cluster., Results: The concept mapping resulted in six distinct clusters, broadly merged in two themes: 1) the 'Person', which included clusters 'Intra-Personal Context and Wellbeing' and 'Family and Social Economic Status' (42 % of all factors) and 2) the 'Society', which included the remaining four clusters 'Policy and Provision', 'Cultural Context and Media', 'Social Support and Modelling', and 'Supportive Environment' (58 % of all factors). Overall, 25 factors were rated as the most impactful on PA behaviours across the life course and being the most modifiable. They were mostly situated in the 'Intra-Personal Context and Wellbeing' cluster. Furthermore, 16 of them were rated as top priority for research., Conclusions: The current framework provides a preliminary overview of factors which may account for PA behaviour across the life course and are most relevant to the European community. These insights could potentially be a foundation for future Pan-European research on how these factors might interact with each other, and assist policy makers to identify appropriate interventions to maximize PA behaviours and thus the health of European citizens.